Triple
T6074426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dana |
E135363
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Dana Delany |
E67291
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Dana Delany | Statement: [Dana, hasNotableBearer, Dana Delany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana Delany Context triple: [Dana, hasNotableBearer, Dana Delany]
-
A.
Dana Delany
chosen
Dana Delany is an American actress best known for her acclaimed work in television dramas such as "China Beach," for which she earned multiple Primetime Emmy Awards.
-
B.
Elizabeth Berkley
Elizabeth Berkley is an American actress best known for her roles in the TV series "Saved by the Bell" and the film "Showgirls."
-
C.
Kate Walsh
Kate Walsh is an American actress best known for her role as Dr. Addison Montgomery on the television series Grey's Anatomy and its spin-off Private Practice.
-
D.
Elizabeth McGovern
Elizabeth McGovern is an American actress and musician best known for her roles in films like "Ragtime" and the television series "Downton Abbey."
-
E.
Téa Leoni
Téa Leoni is an American actress and producer best known for her leading roles in film and television, including the political drama series "Madam Secretary."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c00879e8048190b690717d19c5bc03 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0575d4ed481908eddc88e9b90e22f |
completed | March 22, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16ea8aba881908eb7f8286fbbe272 |
completed | March 23, 2026, 4:47 p.m. |
Created at: March 22, 2026, 4:11 p.m.